Distributed photovoltaic and communication network collaborative regulation method, system, device and medium

Abstract

This invention relates to the field of distribution network operation and control technology, and provides a method, system, device, and medium for coordinated regulation of distributed photovoltaic (PV) power and communication networks. The method includes: constructing an uplink communication resource allocation model and an uplink channel quality model based on a constructed electrical communication spatial mapping relationship; constructing a PV node data transmission delay model based on uplink transmission delay analysis using the uplink communication resource allocation model and the uplink channel quality model; constructing coordinated regulation optimization constraints based on a delay-power coupling model established using Taylor series expansion, and solving a preset coordinated regulation optimization objective function based on these constraints to obtain coordinated regulation commands; and jointly regulating the target distribution network and wireless communication network according to the coordinated regulation commands. This invention, based on a joint scheduling of power grid communication resources and a delay prediction and compensation mechanism, effectively improves the accuracy of voltage control, as well as the safety and stability of distribution network operation.

Description

Technical Field

[0001] This invention relates to the field of power distribution network operation control technology, and in particular to a method, system, equipment and medium for coordinated regulation of distributed photovoltaic and communication networks. Background Technology

[0002] Distributed photovoltaic (PV) power generation is significantly affected by meteorological conditions, exhibiting strong intermittency and volatility. When large-scale distributed PV is connected to the distribution network, the drastic fluctuations in its output power can easily trigger power quality problems such as node voltage exceeding limits and frequent voltage fluctuations, seriously threatening the safe and stable operation of the power grid. Therefore, voltage control technology utilizing the rapid reactive power regulation capability of PV inverters has become a current research hotspot due to its advantages such as fast response speed and low maintenance costs.

[0003] Existing voltage control methods using photovoltaic inverters typically employ a centralized collaborative control approach that aggregates measurement data from the entire network for unified optimization. While this method can theoretically achieve global optimization, the massive number of distributed photovoltaic inverters in active distribution networks rely on wireless communication networks for data transmission and command issuance. Their application performance is highly dependent on the support of real-time communication networks. Furthermore, most collaborative control strategies are based on the assumption of "ideal communication," completely ignoring the bandwidth limitations and transmission delays of communication networks, or simply treating the communication system as a black box with fixed delays, without considering the dynamic impact of communication resource allocation on control performance. However, actual wireless communication resources are extremely limited. When a large number of photovoltaic nodes in the distribution network upload status data at the same time, it is easy to cause network congestion, data queuing, or even packet loss, resulting in a non-negligible random communication transmission delay. This delay can lead to a serious "data expiration" problem, causing the actual optimization analysis measurement data to lag behind the current system's actual operating status. Consequently, the reactive power control commands calculated based on the lagging data may no longer match the current photovoltaic output status when they are issued and executed. This spatiotemporal mismatch not only reduces the accuracy of voltage control, but in severe cases, it can even lead to a deterioration of voltage deviation or oscillation of the control system. Summary of the Invention

[0004] The purpose of this invention is to provide a method for coordinated control of distributed photovoltaic and communication networks. By jointly scheduling power grid communication resources and using a delay prediction and compensation mechanism, the method can achieve precise coordinated control of distribution network voltage while compensating for communication delay deviations, thus solving the voltage control deviation problem caused by communication lag and improving the operational safety and stability of high-proportion photovoltaic distribution networks.

[0005] To achieve the above objectives, it is necessary to provide a method, system, computer equipment, and storage medium for the coordinated control of distributed photovoltaic and communication networks.

[0006] In a first aspect, embodiments of the present invention provide a method for coordinated regulation of distributed photovoltaic power generation and communication networks, the method comprising: Construct an electrical communication spatial mapping relationship between the target distribution network and the wireless communication network, and based on the electrical communication spatial mapping relationship, construct an uplink communication resource allocation model and an uplink channel quality model; Based on the uplink communication resource allocation model and the uplink channel quality model, an uplink transmission delay analysis is performed based on the single data packet size and time slot length to construct a photovoltaic node data transmission delay model. Based on the photovoltaic node data transmission delay model, a delay-power coupling model is established using the Taylor series expansion method. Based on the time delay power coupling model, a coordinated control optimization constraint is constructed, and based on the coordinated control optimization constraint, the preset coordinated control optimization objective function is solved to obtain the corresponding coordinated control command. According to the coordinated control instructions, the target distribution network and the wireless communication network are jointly controlled.

[0007] Furthermore, the electrical communication spatial mapping relationship includes multiple one-to-one correspondences between electrical regions and communication cells; The steps for constructing the electrical communication spatial mapping relationship between the target power distribution network and the wireless communication network include: The wireless communication network is divided into multiple communication cells based on the logical area covered by the signals of each wireless base station within the physical location range corresponding to the target power distribution network. Based on communication coverage constraints, the target distribution network is divided into multiple electrical zones; the communication coverage constraints are to classify bus nodes that are physically located in the same communication cell and whose electrical connection tightness reaches a preset threshold as the same electrical zone; The electrical communication space mapping relationship is obtained based on the mapping relationship between each of the communication cells and each of the electrical regions.

[0008] Furthermore, the step of constructing the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship includes: Based on orthogonal frequency division multiplexing (OFDM) technology, the spectrum resources of the communication cells in the mapping between each electrical region and the communication cell are divided to obtain the uplink subcarrier set; Based on the user information of the electrical region in each electrical region-communication cell mapping pair and the uplink subcarrier set, an uplink subcarrier allocation variable is constructed; The uplink communication resource allocation model is obtained based on the uplink subcarrier allocation variables and the preset channel orthogonality constraints. Based on the uplink communication resource allocation model, uplink power constraints are constructed based on the user-allocated subcarrier transmit power variables. The signal-to-noise ratio (SNR) is calculated based on the preset channel gain model and the user-allocated subcarrier transmit power variable, and the spectral efficiency is mapped based on the obtained SNR to obtain the spectral efficiency model. The uplink channel quality model is obtained based on the spectral efficiency model and the uplink power constraint.

[0009] Furthermore, the step of constructing a photovoltaic node data transmission delay model based on the uplink communication resource allocation model and the uplink channel quality model, and by performing uplink transmission delay analysis based on single data packet size and time slot length, includes: Based on the uplink subcarrier allocation variable in the uplink communication resource allocation model and the spectral efficiency model in the uplink channel quality model, the transmission rate is summarized and analyzed based on the time slot length and the preset subcarrier bandwidth to obtain the total uplink time slot transmission volume of the user. Based on the ratio of the size of a single data packet to the total uplink time slot transmission volume of the user, uplink transmission delay analysis is performed based on the time slot length to obtain the data transmission delay model of the photovoltaic node.

[0010] Furthermore, the step of establishing a time-delay power coupling model based on the Taylor series expansion method according to the photovoltaic node data transmission delay model includes: Based on the photovoltaic node data transmission delay model and the preset controller optimization time, the controller command issuance delay is analyzed to obtain the total control command issuance delay. Based on the total delay of the control command, the active power prediction analysis of each photovoltaic node is performed using the Taylor series expansion method to construct the delay-power coupling model.

[0011] Furthermore, the coordinated regulation and optimization constraints include photovoltaic operation constraints, power balance constraints, AC power flow constraints, and voltage safety constraints; the photovoltaic operation constraints include inverter capacity constraints, active power physical limit constraints, and reactive power regulation capability constraints. The step of constructing collaborative control optimization constraints based on the time-delay power coupling model includes: The photovoltaic node synthesized apparent power is analyzed based on the time-delay power coupling model, and the inverter capacity constraint is constructed based on the obtained node synthesized apparent power and the preset inverter rated capacity. Based on the time-delay power coupling model and the adjustable range of inverter active power, the effectiveness analysis of photovoltaic node active power is carried out, and the active power physical limit constraint is constructed. The reactive power effectiveness of the photovoltaic node is analyzed based on the adjustable range of the inverter reactive power obtained from the preset power factor limitation coefficient and the preset inverter rated capacity, and the reactive power regulation capability constraint is constructed. Based on the aforementioned time-delay power coupling model, node injection power balance analysis is performed on each bus node to construct the power balance constraints. Based on the power balance constraints, voltage-power nonlinear relationship analysis is performed on each bus node to construct the AC power flow constraints. Voltage safety analysis is performed on each bus node to construct the voltage safety constraints.

[0012] Furthermore, the preset collaborative regulation optimization objective function is constructed based on minimizing the voltage deviation of all network nodes as the optimization objective.

[0013] Secondly, embodiments of the present invention provide a distributed photovoltaic and communication network coordinated control system, the system comprising: The mapping construction module is used to construct the electrical communication space mapping relationship between the target distribution network and the wireless communication network, and to construct the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship. The delay analysis module is used to perform uplink transmission delay analysis based on the uplink communication resource allocation model and the uplink channel quality model, and to construct a photovoltaic node data transmission delay model based on the single data packet size and time slot length. The coupling analysis module is used to establish a time-delay power coupling model based on the photovoltaic node data transmission delay model and the Taylor series expansion method. The collaborative optimization module is used to construct collaborative regulation optimization constraints based on the time delay power coupling model, and solve the preset collaborative regulation optimization objective function based on the collaborative regulation optimization constraints to obtain the corresponding collaborative regulation command. The joint control module is used to jointly control the target distribution network and the wireless communication network according to the coordinated control instructions.

[0014] Thirdly, embodiments of the present invention also provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0015] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method.

[0016] This invention provides a method, system, computer device, and storage medium for coordinated control of distributed photovoltaic (PV) and communication networks. The method establishes an electrical communication spatial mapping relationship between a target distribution network and a wireless communication network. Based on this spatial mapping relationship, an uplink communication resource allocation model and an uplink channel quality model are constructed. Then, based on these models, an uplink transmission delay model for PV nodes is constructed using single data packet size and time slot length analysis. Following this model, a delay-power coupling model is established using Taylor series expansion. Coordinated control optimization constraints are then constructed based on these constraints. Finally, a pre-defined coordinated control optimization objective function is solved to obtain corresponding coordinated control commands. Finally, a technical solution is developed for joint control of the target distribution network and the wireless communication network based on these commands. Compared with existing technologies, this distributed photovoltaic and communication network coordinated control method, based on the joint scheduling of power grid communication resources and the delay prediction compensation mechanism, can effectively balance the needs of power control and communication management under limited communication bandwidth resources. While compensating for communication delay deviations, it can achieve precise coordinated control of distribution network voltage. This not only effectively solves the voltage control deviation problem caused by communication lag and improves the accuracy of distribution network voltage control, but also improves the operational safety and stability of high-proportion photovoltaic distribution networks by considering the operational constraints of distribution networks with delays. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the method for coordinated control of distributed photovoltaic and communication networks in an embodiment of the present invention. Figure 2 This is a schematic diagram of the collaborative scheduling architecture of the target power distribution network and the wireless communication network in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of the distributed photovoltaic and communication network coordinated control system in an embodiment of the present invention; Figure 4 This is an internal structural diagram of the computer device in an embodiment of the present invention; The attached figures are labeled as follows: 1. Mapping construction module; 2. Delay analysis module; 3. Coupling analysis module; 4. Collaborative optimization module; 5. Joint control module. Detailed Implementation

[0018] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. Obviously, the embodiments described below are only part of the embodiments of this invention and are used to illustrate the invention, but are not intended to limit the scope of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] The distributed photovoltaic (PV) and communication network coordinated control method provided by this invention can be understood as an optimization method for coordinated control of distribution networks and wireless communication networks. This method addresses the current application situation where existing centralized coordinated control of distributed PV neglects the bandwidth limitations and transmission delays of communication networks, and fails to consider the dynamic impact of communication resource allocation on control performance, resulting in insufficient voltage control accuracy and an inability to guarantee the safe and stable operation of the distribution network. The method proposes a joint modeling approach that integrates voltage regulation requirements at the power level with resource allocation at the communication level, and considers delay prediction compensation. The following embodiments will provide a detailed description of the distributed PV and communication network coordinated control method of this invention.

[0020] In one embodiment, such as Figure 1 As shown, a method for coordinated control of distributed photovoltaic and communication networks is provided, including the following steps: S11. Construct the electrical communication space mapping relationship between the target distribution network and the wireless communication network, and construct the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship; The target distribution network can be understood as the distribution network that actually needs voltage regulation based on distributed photovoltaic inverters. Its core physical layer consists of physical components such as the target distribution network's buses, feeders, distributed photovoltaic systems, and loads. The corresponding wireless communication network can be understood as the wireless network (such as 4G / 5G, WiFi, or ZigBee wireless communication networks) used in the actual target distribution network for data transmission and command issuance to the distributed photovoltaic inverters. It integrates wireless base stations and user terminals deployed at each bus node. The user terminal can be understood as a distributed photovoltaic inverter with real-time measurement and communication functions, as well as intelligent voltage sensors that may be independently deployed at the bus, for data acquisition and command transmission to support the coordinated operation of voltage / reactive power control and wireless resource allocation.

[0021] In this embodiment, the electrical communication spatial mapping relationship can be understood as a one-to-one mapping relationship established between each electrical region and the communication cell in the wireless communication network after the core physical layer of the target distribution network is geographically divided into several independent electrical regions to reduce the complexity of distributed photovoltaic control. This represents the logical and spatial correspondence between the target distribution network physical system and the wireless communication network, including multiple one-to-one mapping pairs of electrical regions and communication cells, laying a reliable architectural foundation for subsequent coordinated control. Specifically, the steps for constructing the electrical communication spatial mapping relationship between the target distribution network and the wireless communication network include: The wireless communication network is divided into multiple communication cells based on the logical area covered by the signals of each wireless base station within the physical location range corresponding to the target power distribution network; that is, the logical area covered by the signals of each wireless base station within the physical location range corresponding to the target power distribution network is regarded as a communication cell, and the number of communication cells is the same as the number of wireless base stations.

[0022] Based on communication coverage constraints, the target distribution network is divided into multiple electrical zones. The communication coverage constraint assigns bus nodes physically located within the same communication cell and with an electrical connection density reaching a preset threshold to the same electrical zone. The electrical connection density can be measured based on the electrical distance between bus nodes, and the calculation of the electrical distance can refer to existing technologies. The corresponding preset threshold can be determined according to actual application requirements. In practical applications, bus nodes within the signal coverage area of ​​the same communication cell in the direct target distribution network with an electrical connection density not less than the preset threshold are grouped into the same electrical zone, until all bus nodes are assigned to a single electrical zone, ultimately resulting in an electrical zone equal to the number of communication cells. Assuming... A , B and E Let the sets of busbars, photovoltaic inverters, and electrical zones be represented respectively. Then, for any specific electrical zone... The bus subset and photovoltaic inverter subset it contains can be represented as follows: and .

[0023] The electrical communication spatial mapping relationship is obtained based on the mapping relationship between each communication cell and each electrical area; that is, the electrical communication spatial mapping relationship is obtained by summing up all the mapping pairs between electrical areas and communication cells corresponding to the target distribution network; based on this electrical communication spatial mapping relationship, combined with the area controller that performs voltage, reactive power and communication resource coordinated scheduling based on distributed photovoltaic inverters and wireless base stations, a system can be formed. Figure 2 The diagram illustrates a hierarchical system architecture for the coordinated regulation of distributed photovoltaic power and communication networks. (Example:) Figure 2As shown, each electrical area uniquely corresponds to a communication cell (single-cell multi-user wireless network) in logical space. In each communication cell, the photovoltaic inverter acts as a communication user node, sending real-time status data to the wireless base station within the cell via the uplink. The wireless base station, acting as the area center node, sends control commands generated by the area controller to each photovoltaic inverter within the corresponding area via the downlink to achieve photovoltaic power output control. It should be noted that... Figure 2 The area controller shown is responsible for unified management and scheduling of communication and power resources based on real-time measurement data from various communication cells, realizing distributed coordination of voltage / reactive power control and wireless resource allocation, and ensuring the coordinated and efficient operation of the distribution network.

[0024] The uplink communication resource allocation model in this embodiment can be understood as further defining the channel resource allocation rules of the wireless communication network based on the electrical communication space mapping relationship constructed above, in order to solve... Figure 2 The communication resource allocation model shown addresses the spectrum contention problem during concurrent transmission of multiple nodes in the uplink. The corresponding uplink channel quality model can be understood as a quantification model of the channel receiver signal quality, constructed by further evaluating the uplink signal quality and transmission capacity based on communication power limitations and the channel environment, after completing the communication resource allocation logic settings. It should be noted that although wireless communication networks using frequency division duplex mode for data interaction involve both uplink and downlink resource allocation and communication quality evaluation, in actual active distribution network applications, only uplink latency affects voltage control accuracy. To improve the efficiency of coordinated regulation optimization, this embodiment preferably only models and analyzes uplink resource allocation and channel quality. If downlink analysis is required based on actual application needs, the uplink modeling and analysis method can be extended accordingly.

[0025] Specifically, the steps of constructing the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship include: Based on orthogonal frequency division multiplexing (OFDM) technology, the spectrum resources of the communication cells in the mapping between each electrical region and the communication cell are divided to obtain the uplink subcarrier set; in practical applications, for any electrical region e The corresponding communication cell divides its available spectrum resources into two mutually orthogonal sets of subcarriers, namely, those containing... The uplink subcarrier set of orthogonal subcarriers, and containing The downlink subcarrier set of orthogonal subcarriers; it should be noted that the spectrum resource allocation based on orthogonal frequency division multiplexing technology can be directly implemented with reference to existing technologies, and will not be described in detail here.

[0026] Based on the user information of the electrical regions in each electrical region-communication cell mapping pair and the uplink subcarrier set, uplink subcarrier allocation variables are constructed; wherein, user information can be understood as the set of communication users involved in the electrical region, including the uplink user set and the downlink user set; for example, for the electrical region e In terms of upstream user set This covers all distributed photovoltaic inverters and smart sensor nodes within the area that need to upload real-time status data such as voltage and power to the wireless base station, and includes downlink user sets. This covers all photovoltaic inverter nodes (PV nodes) within the area that need to receive control commands from wireless base stations. In practical applications, to achieve discrete dynamic scheduling of the aforementioned spectrum resources, this embodiment introduces a binary decision variable as a logical switch characterizing subcarrier occupancy, based on user information and uplink subcarrier sets corresponding to each electrical area. The uplink subcarrier allocation variable is defined as follows: When the variable takes the value 1, it indicates that the first... e The first electrical zone The first uplink user was assigned the first Each uplink subcarrier is used for data transmission. When this variable takes a value of 0, it indicates that the resource has not been allocated. Based on this uplink subcarrier allocation variable, the allocation pattern of uplink spectrum resources on the wireless communication network at any given time can be accurately described. Similarly, the downlink subcarrier allocation variable can also be defined according to requirements. When the variable takes a value of 1, it indicates that the wireless base station sends a signal to the first... The downlink user sent the command, which occupied the first... If the downlink subcarrier allocation variable is 0, then the allocation variable is 0; otherwise, it is 0. Based on this downlink subcarrier allocation variable, the allocation map of downlink spectrum resources of wireless communication network at any time can be accurately described.

[0027] Based on the uplink subcarrier allocation variables and the preset channel orthogonality constraint, the uplink communication resource allocation model is obtained. The preset channel orthogonality constraint can be understood as a resource allocation constraint designed to prevent co-channel interference between different users on the same frequency band, ensuring the reliability and stability of the communication link. For the uplink, it is required that for any given uplink subcarrier, the sum of the allocation variables for that subcarrier by all uplink users must be less than or equal to 1, ensuring that each uplink subcarrier can serve at most one user at any given time. Its mathematical expression is: .

[0028] In practical applications, the pre-set channel orthogonality constraint serves as the physical boundary for uplink communication resource allocation. Combined with uplink subcarrier allocation variables, it yields the corresponding uplink communication resource allocation model, which mathematically guarantees the non-interference of multiple information streams in coordinated control. It should be noted that if the downlink needs to be considered in practical applications, the same uniqueness constraint can be added similarly to ensure that each downlink subcarrier is used to transmit control commands for only one user at a time. Combined with the corresponding downlink subcarrier allocation variables, it yields the corresponding downlink communication resource allocation model, which will not be detailed here.

[0029] Based on the uplink communication resource allocation model, uplink power constraints are constructed based on user-allocated subcarrier transmit power variables. The uplink power constraint can be understood as a physical constraint on communication transmit power established based on the resource allocation logic defined by the uplink subcarrier allocation variables in the uplink communication resource allocation model, taking into account link communication requirements (safe operating conditions of hardware equipment and radio control requirements).

[0030] In practical applications, let's assume we define continuous variables. p To represent the transmit power, we can define... Indicates the first e The first electrical zone The transmit power of each uplink user on the allocated subcarrier is the variable for the transmit power of the allocated subcarrier to the user; for each electrical region of the uplink, the maximum uplink transmit power is set based on the link communication requirements. It also requires that the total transmit power of any uplink user must not exceed the set maximum uplink transmit power. Similarly, it can also define... Indicates that the wireless base station sends to the first The power allocation value for each downlink user transmitting signals, and the maximum downlink transmit power of the set wireless base station. In other words, for the downlink, the sum of the total transmit power allocated by each wireless base station to all corresponding downlink users must not exceed the maximum downlink transmit power of that wireless base station. It should be noted that the above uplink power constraint needs to be considered in conjunction with the uplink subcarrier allocation variable in the uplink communication resource allocation model. Combined statements are used to ensure that the corresponding transmit power is consumed only when a subcarrier is allocated.

[0031] The signal-to-noise ratio (SNR) is calculated based on a preset channel gain model and the user-allocated subcarrier transmit power variable. Then, a spectral efficiency mapping is performed based on the obtained SNR to obtain a spectral efficiency model. The preset channel gain model can be understood as assuming the wireless base station has obtained accurate channel state information (CSI) through channel estimation techniques, and that all receivers have the same noise variance. The normalized channel gain is calculated based on the subcarrier channel coefficients and the background noise variance of the wireless base station receiver, and can be expressed as: In the formula, For electrical area e The corresponding communication cell's number Channel coefficients of each uplink subcarrier; For electrical area e The background noise variance at the receiver of the wireless base station in the corresponding communication cell; For electrical area e The corresponding communication cell's number Normalized channel gain of each uplink subcarrier.

[0032] Based on the aforementioned preset channel gain model, the normalized channel gain of the uplink user on the uplink subcarrier can be determined. The received signal-to-noise ratio on the corresponding subcarrier is obtained by multiplying the normalized channel gain by the user-allocated subcarrier transmit power variable (the uplink user's transmit power on that subcarrier), expressed as: In the formula, For the first The first uplink user in the Received signal-to-noise ratio on each subcarrier.

[0033] After obtaining the received signal-to-noise ratio (SNR), considering the definite positive correlation between the spectral efficiency and SNR of a wireless communication system (the higher the SNR, the higher the information bit rate that can be carried per unit bandwidth), the received SNR can be mapped to the spectral efficiency, which characterizes the data transmission capability under the current channel conditions. It should be noted that in this embodiment, to facilitate the subsequent construction and solution of the collaborative optimization model, a correction function based on Shannon's formula is used to construct the mapping relationship between spectral efficiency and SNR, describing the theoretical maximum spectral efficiency that the channel can support under a given bit error rate requirement. Its mathematical expression is: In the formula, For the first The first uplink user in the Received signal-to-noise ratio on each subcarrier; This is a bandwidth efficiency adjustment factor used to characterize the coding loss of a real communication network; This is the signal-to-noise ratio difference, which is related to the preset target bit error rate of the communication network; For the first The spectral efficiency on each subcarrier, represented by this continuous function expression, characterizes the mapping relationship between spectral efficiency and signal-to-noise ratio, and can smoothly transform the channel quality of the physical layer into a data transmission capability indicator.

[0034] The uplink channel quality model is obtained based on the spectral efficiency model and the uplink power constraint.

[0035] The spectral efficiency model in this embodiment can characterize the actual data transmission rate of each subcarrier under the current power configuration. It is used as a key input parameter for calculating the uplink data transmission delay, thereby establishing a mathematical relationship between physical power control and data transmission performance, and providing reliable technical support for subsequent collaborative regulation and optimization based on communication delay consideration.

[0036] S12. Based on the uplink communication resource allocation model and the uplink channel quality model, perform uplink transmission delay analysis based on single data packet size and time slot length, and construct a photovoltaic node data transmission delay model; wherein, the single data packet size can be understood as the data volume of a single uplink data packet in the wireless communication network, which can be determined by the type of electrical quantity and data accuracy collected by the photovoltaic inverter in the actual application scenario, and the time slot length can be determined by the subcarrier bandwidth and physical layer frame structure of the wireless communication network, which is not specifically limited here.

[0037] The photovoltaic node data transmission delay model in this embodiment can be understood as a mathematical model that comprehensively considers the data load characteristics of the wireless communication network, the allocated spectrum bandwidth resources, and the current channel quality status to quantitatively evaluate the specific time lag required for the distributed photovoltaic inverter to upload real-time sensed voltage, power, and other status data to the area controller. Specifically, the steps of constructing the photovoltaic node data transmission delay model based on the uplink communication resource allocation model and the uplink channel quality model, and based on the single data packet size and time slot length for uplink transmission delay analysis, include: Based on the uplink subcarrier allocation variables in the uplink communication resource allocation model and the spectral efficiency model in the uplink channel quality model, a transmission rate summary analysis is performed based on the time slot length and preset subcarrier bandwidth to obtain the total uplink time slot transmission volume for the user. The total uplink time slot transmission volume can be understood as the actual data carrying capacity of a single uplink user (photovoltaic inverter node) on all allocated subcarriers within the electrical area of ​​the time slot length. In practical applications, using the uplink subcarrier allocation variables and the spectral efficiency of each subcarrier calculated based on the spectral efficiency model, the transmission rates (the product of subcarrier bandwidth and corresponding spectral efficiency) of all subcarriers occupied by a certain user are summed to obtain the corresponding actual transmission rate. Then, based on the product of the actual transmission rate and the time slot length, the corresponding total uplink time slot transmission volume for the user is obtained, which can be expressed as: In the formula, For electrical area e The corresponding communication cell's number Spectral efficiency of each subcarrier; The preset subcarrier bandwidth, which determines the basic carrying capacity of a single channel; The time slot length; For electrical area e The Total uplink timeslot transmission of each uplink user.

[0038] Based on the ratio of the single data packet size to the total uplink time slot transmission volume of the user, uplink transmission delay analysis is performed based on the time slot length to obtain the photovoltaic node data transmission delay model. The uplink transmission delay analysis can be understood as obtaining the theoretical time required for data transmission based on the ratio of the single data packet size to the total uplink time slot transmission volume of each user, and then mapping the theoretical time to a discrete number of time slots. Considering that data transmission in a communication network must occupy an integer number of time slots, an up-rounding function is introduced in the theoretical time calculation to round the final uplink transmission delay analysis result to an integer multiple of the time slot length. Therefore, the photovoltaic node data transmission delay model can be expressed as: In the formula, Size of a single data packet; For electrical area e The Effective transmission latency for each uplink user.

[0039] The photovoltaic node data transmission delay model constructed in this embodiment can accurately quantify the physical time required for the state data to be sent from the photovoltaic inverter and fully received by the corresponding wireless base station under the current resource allocation strategy and channel state. This delay value will be used as the key time variable input for the subsequent delay-power coupling model to correct the control deviation caused by communication lag, so as to avoid problems such as voltage deviation deterioration or control system oscillation caused by the inability of the reactive power control command calculated based on the lag data to match the photovoltaic output state at the time of execution of the command. This provides a reliable guarantee for improving the voltage control accuracy.

[0040] S13. Based on the photovoltaic node data transmission delay model, a time-delay power coupling model is established using the Taylor series expansion method. This model can be understood as a data model that calculates the actual photovoltaic output at the time the control command is executed based on the current measurement status data and its changing trend. To effectively compensate for the delay in the measurement data actually received by the area controller and address the data expiration problem caused by time delay, this embodiment preferably determines the time span between the data acquisition time and the future execution time when the area controller generates and issues the control command, based on known information at the data acquisition time. Then, using the Taylor series expansion method, the predicted active power value of any photovoltaic inverter node in each electrical area at the future time is calculated accordingly.

[0041] Specifically, the step of establishing a time-delay-power coupling model based on the Taylor series expansion method according to the photovoltaic node data transmission delay model includes: Based on the photovoltaic node data transmission delay model and the preset controller optimization time, the controller command issuance delay is analyzed to obtain the total control command issuance delay. The preset controller optimization time can be understood as the computational processing delay required for the regional controller to solve the collaborative optimization problem. It can be determined based on actual optimization problem solving experience combined with the controller hardware computing performance, and is not specifically limited here. The corresponding total control command issuance delay, based on actual application scenario analysis, consists of two parts: the uplink data transmission delay of the wireless communication network quantified by the aforementioned photovoltaic node data transmission delay model and the preset controller optimization time. Its mathematical expression is: In the formula, For electrical area e Total delay in issuing control commands (i.e., the total closed-loop time from sensing to execution). Optimize the duration for the preset controller; The downlink command transmission delay (usually small and can be considered a constant or included in the margin) can be set based on the actual application. For electrical area e Uplink user set The Middlek ( ) uplink users; For electrical area e The k Effective transmission latency for each uplink user; Indicates electrical area e The maximum value among all uplink users (PV nodes) in the system.

[0042] Based on the total delay of the control command issuance, the active power prediction analysis of each photovoltaic node is performed using the Taylor series expansion method to construct the time-delay power coupling model. The time-delay power coupling model is used to characterize the mathematical expression representing the predicted active power of the photovoltaic inverter at the future command issuance time based on the total delay of the control command issuance, and can be expressed as: In the formula, For electrical area e The timing of future command issuance; The moment when the photovoltaic inverter node uploads measurement status data; Let t be the photovoltaic inverter node b The actual active power measurement value transmitted; n Represents the order of the Taylor expansion; Indicates photovoltaic inverter node b The active power at time t n First derivative ( n =1) characterizes the instantaneous rate of change of photovoltaic output, while higher-order derivatives further correct the acceleration and curvature characteristics of the change; For electrical area e The future command issuance time has a total delay in the issuance of control commands. Photovoltaic inverter nodes b The predicted value of active power.

[0043] This embodiment, based on the Taylor series expansion method, constructs a time-delay power coupling model that addresses the contradiction between rapid changes in actual photovoltaic power output and slow communication transmission. It accurately predicts the photovoltaic state at the time of command execution based on current measurement data and its changing trends, and effectively compensates for the time delay of photovoltaic active power data used in controller regulation and optimization analysis. This provides a reliable data foundation for subsequent collaborative regulation and optimization analysis, thereby effectively solving the voltage control deviation problem caused by communication lag.

[0044] S14. Based on the time-delay power coupling model, construct collaborative control optimization constraints, and solve the preset collaborative control optimization objective function according to the collaborative control optimization constraints to obtain the corresponding collaborative control command; wherein, the collaborative control optimization constraints can be understood as the determination of the data transmission rate when considering the existence of uplink transmission delay, and the transmission delay is determined by the uplink subcarrier allocation variable and the user-allocated subcarrier transmit power variable, and the transmission delay will change the active power prediction value of the photovoltaic inverter through the time-delay power coupling model, and the change in active power value limits the upper limit of reactive power that the photovoltaic inverter can output, in order to ensure the feasibility of the scheduling command at the physical level and establish the coupling relationship between variables, the physical operation constraints are constructed to ensure the safe and stable operation of the target distribution network.

[0045] In this preferred embodiment, the coordinated regulation and optimization constraints include photovoltaic operation constraints, power balance constraints, AC power flow constraints, and voltage safety constraints. The photovoltaic operation constraints consider the impact of photovoltaic active power on photovoltaic equipment during the time delay period, ensuring that under any communication lag scenario, the issued control commands will not exceed the physical tolerance limits of the photovoltaic equipment, thereby effectively guaranteeing the safe and stable operation of the photovoltaic equipment. These constraints include inverter capacity constraints, active power physical limit constraints, and reactive power regulation capability constraints. Specifically, the step of constructing the coordinated regulation and optimization constraints based on the time delay power coupling model includes: Based on the aforementioned time-delay power coupling model, the synthesized apparent power of photovoltaic nodes is analyzed, and the inverter capacity constraint is constructed according to the obtained synthesized apparent power of the nodes and the preset rated capacity of the inverter. The synthesized apparent power of the nodes can be calculated based on the sum of the squares of the reactive power output by the photovoltaic inverter and the active power predicted based on the time-delay power coupling model. The corresponding preset rated capacity of the inverter can be determined based on the rated capacity of the actual photovoltaic inverter. Therefore, the inverter capacity constraint can be expressed as: In the formula, For electrical area e The future command issuance time has a total delay in the issuance of control commands. Photovoltaic inverter nodes b The predicted value of active power; For electrical area e Internal photovoltaic inverter node b When the command is issued in the future The output reactive power value; For electrical area e Internal photovoltaic inverter node b The preset rated capacity of the inverter.

[0046] Based on the aforementioned time-delay power coupling model and the adjustable range of inverter active power, an active power effectiveness analysis of the photovoltaic node is performed, and the active power physical limit constraint is constructed. The adjustable range of inverter active power can be determined based on the minimum and maximum allowable active power of the actual photovoltaic inverter. The corresponding active power physical limit constraint can be understood as the condition ensuring that the predicted active power is within the adjustable range of inverter active power, and can be expressed as: In the formula, and Electrical areas e Internal photovoltaic inverter node b The lower and upper limits of the adjustable range of the inverter's active power.

[0047] The reactive power effectiveness of photovoltaic nodes is analyzed based on the adjustable range of inverter reactive power obtained from a preset power factor limit coefficient and a preset inverter rated capacity, thus constructing the reactive power regulation capability constraint. The preset power factor limit coefficient can be determined based on the actual application scenario, and the adjustable range of inverter reactive power can be determined based on the product of the preset power factor limit coefficient and the preset inverter rated capacity. The corresponding reactive power regulation capability constraint can be expressed as: In the formula, This is the preset power factor limiting coefficient.

[0048] Based on the aforementioned time-delay power coupling model, node-injected power balance analysis is performed on each bus node to construct the power balance constraints. These constraints can be understood as node power balance equations constructed based on the power flow relationships within the target distribution network, including node-injected active power balance equations and node-injected reactive power balance equations, which can be expressed as: in, and Electrical areas e When the command is issued in the future bus node i The net active power injection and net reactive power injection of a photovoltaic node can be expressed as the difference between the actual photovoltaic power and the load power. The actual photovoltaic power of a bus node that is not connected to a photovoltaic inverter is considered to be 0, and the corresponding net injection is the difference between 0 and the load power. and For electrical area e When the command is issued in the future bus node iThe active power load demand and the active power load demand of nodes.

[0049] Based on the power balance constraints, voltage-power nonlinear relationship analysis is performed on each bus node to construct the AC power flow constraints. The AC power flow constraints can be understood as constraint equations describing the nonlinear relationship between node voltage and power, determined by AC power flow analysis based on injected power at the bus nodes. These equations can be expressed as: In the formula, and Electrical areas e Inner bus node i With bus node j The electrical conductance and susceptance between them; and Electrical areas e Inner bus node i With bus node j When the command is issued in the future The voltage phase angle; and Electrical areas e Inner bus node i With bus node j When the command is issued in the future The actual voltage.

[0050] It should be noted that, based on the above AC power flow constraints, when changes in uplink communication delay cause changes in the predicted active power or reactive power, it will inevitably cause changes in the injected power at the nodes, thereby forcing changes in the voltage amplitude at the corresponding nodes through AC power flow constraints.

[0051] Voltage safety analysis is performed on each bus node to construct the voltage safety constraints. These voltage safety constraints can be understood as operational constraints requiring the voltage amplitude of all bus nodes in the entire network to remain within a safe operating range to ensure the safe operation of the target distribution network. They can be expressed as: In the formula, and These are the minimum allowable voltage amplitude and the maximum allowable voltage amplitude, respectively.

[0052] This embodiment is based on a collaborative control optimization constraint constructed using a time delay compensation mechanism that actively predicts photovoltaic active power. It can break through the ideal assumption of existing optimization constraints based on the real-time accuracy of the analyzed data. By using uplink communication delay as the basis for constructing collaborative control optimization constraints, it can effectively avoid the spatiotemporal mismatch problem caused by data expiration due to communication delay, which makes the reactive power control command calculated based on the lagging data unable to match the current photovoltaic output status. It fundamentally suppresses the risk of voltage deviation deterioration or oscillation caused by improper control, ensures the effectiveness and safety of the command at the time of execution, and significantly improves the voltage control accuracy and system stability.

[0053] The preset coordinated control optimization objective function in this embodiment can be understood as an optimization objective set based on the actual target distribution network voltage control requirements. In order to ensure optimal allocation of communication resources and reliable generation of voltage control commands under limited communication bandwidth, this embodiment preferably constructs the preset coordinated control optimization objective function based on minimizing the voltage deviation of all nodes in the entire network as the optimization objective, that is, minimizing the sum of voltage deviations of all bus nodes in all electrical areas, which can be expressed as: In the formula, For electrical area e Inner bus node i When the command is issued in the future The actual voltage; This is the system reference voltage; The set of decision variables includes the reactive power of the photovoltaic inverter, the uplink subcarrier allocation variable, and the user-allocated subcarrier transmit power variable.

[0054] Based on the aforementioned coordinated regulation and optimization constraints, the preset coordinated regulation and optimization objective function is solved to obtain the corresponding coordinated regulation and control instructions; Based on the above methods and steps, the collaborative regulation optimization constraints and the preset collaborative regulation optimization objective function can be combined to obtain a collaborative optimization model suitable for the deployment of area controllers. In practical applications, existing numerical optimization algorithms can be used to solve for a joint scheduling strategy that includes optimal communication subcarrier allocation, transmit power allocation, and photovoltaic inverter reactive power setpoints. This strategy is then converted into a collaborative regulation command that is synchronously sent to each wireless base station and distributed photovoltaic inverters to drive the wireless base stations to optimize the transmission channels and control the inverters to output the target reactive power. In other words, the above solution can calculate the optimal voltage regulation command and allocate the fastest communication channels to key nodes, minimizing communication latency.

[0055] S15. According to the coordinated control instruction, the target distribution network and the wireless communication network are jointly controlled; wherein, the joint control can be understood as the coordinated control of the target reactive power output of the distributed photovoltaic inverters of the target distribution network and the transmission channel optimization of the wireless base station. Based on the execution of the coordinated control instruction, under the condition of limited communication bandwidth, the power grid communication resources can be jointly scheduled by introducing a time delay prediction compensation mechanism to automatically balance the needs of power control and communication management, and realize the precise coordinated control of the distribution network voltage.

[0056] This invention provides an electrical communication spatial mapping relationship between a target distribution network and a wireless communication network. Based on this mapping relationship, an uplink communication resource allocation model and an uplink channel quality model are constructed. Then, based on these models, an uplink transmission delay analysis is performed using single data packet size and time slot length to construct a photovoltaic node data transmission delay model. Following this model, a delay-power coupling model is established using Taylor series expansion. Based on this model, collaborative regulation optimization constraints are constructed. Based on these constraints, a preset collaborative regulation optimization objective function is solved to obtain corresponding collaborative regulation commands. Finally, a scheme for joint regulation of the target distribution network and the wireless communication network is provided. Based on the joint scheduling of power grid communication resources and a delay prediction compensation mechanism, this invention effectively balances power control and communication management needs under limited communication bandwidth resources. While compensating for communication delay deviations, it achieves precise collaborative control of the distribution network voltage. This not only effectively solves the voltage control deviation problem caused by communication lag and improves the accuracy of distribution network voltage control, but also enhances the operational safety and stability of high-proportion photovoltaic distribution networks by considering the operational constraints of the distribution network with delay.

[0057] It should be noted that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise explicitly stated in this document, there is no strict order requirement for the execution of these steps, and they can be executed in other orders.

[0058] In one embodiment, such as Figure 3 As shown, a distributed photovoltaic and communication network coordinated control system is provided, the system comprising: Mapping construction module 1 is used to construct the electrical communication space mapping relationship between the target distribution network and the wireless communication network, and to construct the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship; The delay analysis module 2 is used to perform uplink transmission delay analysis based on the uplink communication resource allocation model and the uplink channel quality model, and to construct a photovoltaic node data transmission delay model based on the single data packet size and time slot length. Coupling analysis module 3 is used to establish a time delay power coupling model based on the Taylor series expansion method according to the photovoltaic node data transmission delay model; The collaborative optimization module 4 is used to construct collaborative regulation optimization constraints based on the time delay power coupling model, and solve the preset collaborative regulation optimization objective function based on the collaborative regulation optimization constraints to obtain the corresponding collaborative regulation command. The joint control module 5 is used to jointly control the target distribution network and the wireless communication network according to the coordinated control instructions.

[0059] In one embodiment, the electrical communication spatial mapping relationship includes multiple one-to-one correspondences between electrical regions and communication cells; the construction of the electrical communication spatial mapping relationship between the target distribution network and the wireless communication network includes: The wireless communication network is divided into multiple communication cells based on the logical area covered by the signals of each wireless base station within the physical location range corresponding to the target power distribution network. Based on communication coverage constraints, the target distribution network is divided into multiple electrical zones; the communication coverage constraints are to classify bus nodes that are physically located in the same communication cell and whose electrical connection tightness reaches a preset threshold as the same electrical zone; The electrical communication space mapping relationship is obtained based on the mapping relationship between each of the communication cells and each of the electrical regions.

[0060] In one embodiment, constructing the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship includes: Based on orthogonal frequency division multiplexing (OFDM) technology, the spectrum resources of the communication cells in the mapping between each electrical region and the communication cell are divided to obtain the uplink subcarrier set; Based on the user information of the electrical region in each electrical region-communication cell mapping pair and the uplink subcarrier set, an uplink subcarrier allocation variable is constructed; The uplink communication resource allocation model is obtained based on the uplink subcarrier allocation variables and the preset channel orthogonality constraints. Based on the uplink communication resource allocation model, uplink power constraints are constructed based on the user-allocated subcarrier transmit power variables. The signal-to-noise ratio (SNR) is calculated based on the preset channel gain model and the user-allocated subcarrier transmit power variable, and the spectral efficiency is mapped based on the obtained SNR to obtain the spectral efficiency model. The uplink channel quality model is obtained based on the spectral efficiency model and the uplink power constraint.

[0061] In one embodiment, the step of constructing a photovoltaic node data transmission delay model based on the uplink communication resource allocation model and the uplink channel quality model, using single data packet size and time slot length for uplink transmission delay analysis, includes: Based on the uplink subcarrier allocation variable in the uplink communication resource allocation model and the spectral efficiency model in the uplink channel quality model, the transmission rate is summarized and analyzed based on the time slot length and the preset subcarrier bandwidth to obtain the total uplink time slot transmission volume of the user. Based on the ratio of the size of a single data packet to the total uplink time slot transmission volume of the user, uplink transmission delay analysis is performed based on the time slot length to obtain the data transmission delay model of the photovoltaic node.

[0062] In one embodiment, establishing a time-delay-power coupling model based on the Taylor series expansion method according to the photovoltaic node data transmission delay model includes: Based on the photovoltaic node data transmission delay model and the preset controller optimization time, the controller command issuance delay is analyzed to obtain the total control command issuance delay. Based on the total delay of the control command, the active power prediction analysis of each photovoltaic node is performed using the Taylor series expansion method to construct the delay-power coupling model.

[0063] In one embodiment, the coordinated regulation optimization constraints include photovoltaic operation constraints, power balance constraints, AC power flow constraints, and voltage safety constraints; the photovoltaic operation constraints include inverter capacity constraints, active power physical limit constraints, and reactive power regulation capability constraints; the construction of coordinated regulation optimization constraints based on the time-delay power coupling model includes: The photovoltaic node synthesized apparent power is analyzed based on the time-delay power coupling model, and the inverter capacity constraint is constructed based on the obtained node synthesized apparent power and the preset inverter rated capacity. Based on the time-delay power coupling model and the adjustable range of inverter active power, the effectiveness analysis of photovoltaic node active power is carried out, and the active power physical limit constraint is constructed. The reactive power effectiveness of the photovoltaic node is analyzed based on the adjustable range of the inverter reactive power obtained from the preset power factor limitation coefficient and the preset inverter rated capacity, and the reactive power regulation capability constraint is constructed. Based on the aforementioned time-delay power coupling model, node injection power balance analysis is performed on each bus node to construct the power balance constraints. Based on the power balance constraints, voltage-power nonlinear relationship analysis is performed on each bus node to construct the AC power flow constraints. Voltage safety analysis is performed on each bus node to construct the voltage safety constraints.

[0064] In one embodiment, the preset collaborative regulation optimization objective function is constructed based on minimizing the voltage deviation of all network nodes as the optimization objective.

[0065] Specific limitations regarding the coordinated control system of distributed photovoltaic (PV) and communication networks can be found in the limitations of the coordinated control method of distributed PV and communication networks described above; the corresponding technical effects are equivalent and will not be repeated here. Each module in the aforementioned coordinated control system of distributed PV and communication networks can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0066] Figure 4 An internal structural diagram of a computer device is shown in one embodiment. This computer device may specifically be a terminal or a server. Figure 4 As shown, the computer device includes a processor, memory, network interface, display, camera, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it can implement a method for coordinated control of distributed photovoltaic and communication networks. The display screen can be an LCD screen or an e-ink display screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0067] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computing device may include more or fewer components than those shown in the figure, or combine certain components, or have the same component arrangement.

[0068] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0069] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0070] In summary, the distributed photovoltaic and communication network coordinated control method, system, computer equipment, and storage medium provided by the embodiments of the present invention, based on the joint scheduling of power grid communication resources and the delay prediction compensation mechanism, can effectively balance the needs of power control and communication management under limited communication bandwidth resources. While compensating for communication delay deviations, it can achieve precise coordinated control of distribution network voltage. This not only effectively solves the voltage control deviation problem caused by communication lag and improves the accuracy of distribution network voltage control, but also improves the operational safety and stability of high-proportion photovoltaic distribution networks based on considering the operational constraints of distribution networks with delays.

[0071] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0072] The above-described embodiments are merely preferred embodiments of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention. Therefore, the scope of protection of this invention should be determined by the scope of the claims.

Claims

1. A method for coordinated control of distributed photovoltaic power generation and communication networks, characterized in that, The method includes: Construct an electrical communication spatial mapping relationship between the target distribution network and the wireless communication network, and based on the electrical communication spatial mapping relationship, construct an uplink communication resource allocation model and an uplink channel quality model; Based on the uplink communication resource allocation model and the uplink channel quality model, an uplink transmission delay analysis is performed based on the single data packet size and time slot length to construct a photovoltaic node data transmission delay model. Based on the photovoltaic node data transmission delay model, a delay-power coupling model is established using the Taylor series expansion method. Based on the time delay power coupling model, a coordinated control optimization constraint is constructed, and based on the coordinated control optimization constraint, the preset coordinated control optimization objective function is solved to obtain the corresponding coordinated control command. According to the coordinated control instructions, the target distribution network and the wireless communication network are jointly controlled.

2. The method for coordinated control of distributed photovoltaic and communication networks as described in claim 1, characterized in that, The electrical communication spatial mapping relationship includes multiple one-to-one correspondences between electrical regions and communication cells; The steps for constructing the electrical communication spatial mapping relationship between the target power distribution network and the wireless communication network include: The wireless communication network is divided into multiple communication cells based on the logical area covered by the signals of each wireless base station within the physical location range corresponding to the target power distribution network. Based on communication coverage constraints, the target distribution network is divided into multiple electrical zones; the communication coverage constraints are to classify bus nodes that are physically located in the same communication cell and whose electrical connection tightness reaches a preset threshold as the same electrical zone; The electrical communication space mapping relationship is obtained based on the mapping relationship between each of the communication cells and each of the electrical regions.

3. The method for coordinated control of distributed photovoltaic and communication networks as described in claim 2, characterized in that, The steps of constructing the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship include: Based on orthogonal frequency division multiplexing (OFDM) technology, the spectrum resources of the communication cells in the mapping between each electrical region and the communication cell are divided to obtain the uplink subcarrier set; Based on the user information of the electrical region in each electrical region-communication cell mapping pair and the uplink subcarrier set, an uplink subcarrier allocation variable is constructed; The uplink communication resource allocation model is obtained based on the uplink subcarrier allocation variables and the preset channel orthogonality constraints. Based on the uplink communication resource allocation model, uplink power constraints are constructed based on the user-allocated subcarrier transmit power variables. The signal-to-noise ratio (SNR) is calculated based on the preset channel gain model and the user-allocated subcarrier transmit power variable, and the spectral efficiency is mapped based on the obtained SNR to obtain the spectral efficiency model. The uplink channel quality model is obtained based on the spectral efficiency model and the uplink power constraint.

4. The method for coordinated control of distributed photovoltaic and communication networks as described in claim 3, characterized in that, The steps of constructing a photovoltaic node data transmission delay model based on the uplink communication resource allocation model and the uplink channel quality model, and based on single data packet size and time slot length for uplink transmission delay analysis, include: Based on the uplink subcarrier allocation variable in the uplink communication resource allocation model and the spectral efficiency model in the uplink channel quality model, the transmission rate is summarized and analyzed based on the time slot length and the preset subcarrier bandwidth to obtain the total uplink time slot transmission volume of the user. Based on the ratio of the size of a single data packet to the total uplink time slot transmission volume of the user, uplink transmission delay analysis is performed based on the time slot length to obtain the data transmission delay model of the photovoltaic node.

5. The method for coordinated control of distributed photovoltaic and communication networks as described in claim 4, characterized in that, The step of establishing a time-delay power coupling model based on the photovoltaic node data transmission delay model and the Taylor series expansion method includes: Based on the photovoltaic node data transmission delay model and the preset controller optimization time, the controller command issuance delay is analyzed to obtain the total control command issuance delay. Based on the total delay of the control command, the active power prediction analysis of each photovoltaic node is performed using the Taylor series expansion method to construct the delay-power coupling model.

6. The method for coordinated control of distributed photovoltaic and communication networks as described in claim 1, characterized in that, The coordinated regulation and optimization constraints include photovoltaic operation constraints, power balance constraints, AC power flow constraints, and voltage safety constraints; the photovoltaic operation constraints include inverter capacity constraints, active power physical limit constraints, and reactive power regulation capability constraints. The step of constructing collaborative control optimization constraints based on the time-delay power coupling model includes: The photovoltaic node synthesized apparent power is analyzed based on the time-delay power coupling model, and the inverter capacity constraint is constructed based on the obtained node synthesized apparent power and the preset inverter rated capacity. Based on the time-delay power coupling model and the adjustable range of inverter active power, the effectiveness analysis of photovoltaic node active power is carried out, and the active power physical limit constraint is constructed. The reactive power effectiveness of the photovoltaic node is analyzed based on the adjustable range of the inverter reactive power obtained from the preset power factor limitation coefficient and the preset inverter rated capacity, and the reactive power regulation capability constraint is constructed. Based on the aforementioned time-delay power coupling model, node injection power balance analysis is performed on each bus node to construct the power balance constraints. Based on the power balance constraints, voltage-power nonlinear relationship analysis is performed on each bus node to construct the AC power flow constraints. Voltage safety analysis is performed on each bus node to construct the voltage safety constraints.

7. The method for coordinated control of distributed photovoltaic and communication networks as described in claim 1, characterized in that, The preset collaborative regulation optimization objective function is constructed based on minimizing the voltage deviation of all network nodes as the optimization objective.

8. A distributed photovoltaic and communication network coordinated control system, characterized in that, The system includes: The mapping construction module is used to construct the electrical communication space mapping relationship between the target distribution network and the wireless communication network, and to construct the uplink communication resource allocation model and the uplink channel quality model based on the electrical communication space mapping relationship. The delay analysis module is used to perform uplink transmission delay analysis based on the uplink communication resource allocation model and the uplink channel quality model, and to construct a photovoltaic node data transmission delay model based on the single data packet size and time slot length. The coupling analysis module is used to establish a time-delay power coupling model based on the photovoltaic node data transmission delay model and the Taylor series expansion method. The collaborative optimization module is used to construct collaborative regulation optimization constraints based on the time delay power coupling model, and solve the preset collaborative regulation optimization objective function based on the collaborative regulation optimization constraints to obtain the corresponding collaborative regulation command. The joint control module is used to jointly control the target distribution network and the wireless communication network according to the coordinated control instructions.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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